To support a national security mission, the full-time Audio AI Engineer will optimize and adapt multilingual speech-to-text models for mobile devices, ensuring high performance and accuracy while collaborating with mobile engineering teams.
Key Responsibilities
Ingest, clean, segment, label, and version multilingual audio and transcript data, focusing on code-switching and borrowed-word phenomena
Fine-tune and compress large ASR models to meet iPhone-class memory, latency, and battery constraints while maintaining transcription quality
Design model packaging for dynamic, per-language deployment based on use-case context and build evaluation pipelines to assess model performance
Required Qualifications
Bachelor's degree in Computer Science, Data Science, Machine Learning, Computational Linguistics, or a closely related field
Strong data-engineering background with experience in building production pipelines for large audio/text datasets
Hands-on experience fine-tuning or adapting speech/audio models using parameter-efficient methods and model compression techniques
Practical experience with ASR/speech-to-text model development and evaluation across multiple languages
Strong Python and SQL skills; familiarity with PyTorch, Hugging Face Transformers/PEFT, and related tools